International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 6 Issue: 7 98 - 101 ______A Landmark Based Shortest Path Detection by Using A* and Haversine Formula
Ms. Megha G. Mathpal Department of Information Technology Government Engineering College Modasa, Gujarat, India [email protected]
Abstract—In 1900, less than 20 percent of the world populace lived in cities, in 2007, fair more than 50 percent of the world populace lived in cities. In 2050, it has been anticipated that more than 70 percent of the worldwide population (about 6.4 billion individuals) will be city tenants. There's more weight being set on cities through this increment in population [1]. With approach of keen cities, data and communication technology is progressively transforming the way city regions and city inhabitants organize and work in reaction to urban development. In this paper, we create a nonspecific plot for navigating a route throughout city
A asked route is given by utilizing combination of A* Algorithm and Haversine equation. Haversine Equation gives least distance between any two focuses on spherical body by utilizing latitude and longitude. This least distance is at that point given to A* calculation to calculate minimum distance. The method for identifying the shortest path is specify in this paper.
Keywords- Haversine Formula, Dijkstra Algorithm, Google Map, XML.
______*****______I. INTRODUCTION II. PROBLEM DEFINATION The downsides happened in past paper of shortest path The Point of Paper is to discover out the route in between two discovery by utilizing Dijkstra calculation is recuperated in spots/junctions inside a city entered by client by making use of this paper by employing A* calculation. A* calculation is the Intersections in between the Source and Goal spots/junctions. heuristic in nature. The point of Paper is to discover the route The main motto behind it is to progress the navigation of client between two places inside a city entered by client utilizing inside a city; particularly in Indian cities where Town Arranging the Intersections between Source and Goal intersections. The approach doesn’t take after a standard rule for numbering or witticism behind it is to progress navigation of client inside a naming the distinctive spots or places. Most of the times an city; particularly in India where Town Arranging approach obscure individual can’t discover indeed the most famous places doesn’t take after a standard rule for naming the diverse inside the city due to nonappearance of naming sheets or other places. Most of the times an unknown person can’t discover noteworthy identities. Subsequently the project is intended to indeed the foremost popular places inside the city due to allow a suitable route to client by coordinating it through various nonappearance of noteworthy identities. Hence the paper is junctions and streets which is able be easily identified by the planning to allow a suitable route to client by coordinating it related landmarks given with the route. The requested route is through different intersections and streets which will be given to client in terms of the intersections present in between the effortlessly distinguished by the related landmarks and a Google map. The route is given in two parts as: 1) Content source and goal route along with landmarks and streets route containing route giving a intersection to intersection interfacing them. The Landmarks utilized within the route may be movement to client in conjunction with the appropriate noteworthy Buildings, Statues, Streets, Complexes, Landmarks, directions and turnings directing the client to induce the Sanctuaries, etc. The use of Landmarks includes an advantage of precise halfway intersections or landmarks 2) Google Map getting to the exact place having no critical personality whereas for correct requested route. Paper uses client-server voyaging through route provided to client making the application engineering. Communication between them is entirely in friendly to the client obscure of the city to discover out the route XML for adaptability. The client has client interface from in between any two spots or intersections within the city. The where an input is taken in XML for processing. The server application is bound to deliver the shortest route providing a comprises of a Java Processing Application and Database for junction to junction movement to client in conjunction with the it. The Database utilized by handling application could be a appropriate directions and turnings directing the client to induce Social database containing whole information around city. the precise intermediate intersections (with their significant The processing application after parsing request computes landmarks) or landmarks in specific zones in between two route between them with all necessary subtle elements with junctions/spots provided by client. Latitude/Longitude for Google map and sends it as XML response. Client once more parsing response gets it on Client Interface with Google map handling done in JavaScript.
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IJRITCC | July 2018, Available @ http://www.ijritcc.org ______International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 6 Issue: 7 98 - 101 ______III. LITERATURE SURVEY closedset := the empty set // The set of nodes already evaluated. This paper contains “great circle distance” which speaks to openset := {start} // The set of tentative nodes to be evaluated, the shortest path for distance modeling and optimal facility initially containing the start node area on spherical surface. Great circle distances take into came_from := the empty map // The map of navigated nodes. consideration the geometrical reality of the spherical Earth g_score[start] := 0 // Cost from start along best known path. and offers an elective to broadly held idea that travel over // Estimated total cost from start to goal through y. water can be precisely displayed by Euclidean distances. The f_score[start] := g_score[start] + heuristic_cost_estimate(start, need for geometrical presentation of the spherical earth gets goal) while openset is not empty current: = the node in openset having the lowest f_score[] value to be exceptionally important when we take into thought an if current = goal ever-expanding junction inside a city. The utilize of “Great return reconstruct_path(came_from, goal) circle distances” opens another avenue for merging of remove current from openset Navigation and Spherical Trigonometry into progression of add current to closedset logistics and facility location. In this paper an assessment of for each neighbour in neighbor_nodes(current) distance area utilizing great circle distances is utilized to tentative_g_score:=g_score[current]+ illustrate the application of the concept [4][3]. This paper dist_between(current,neighbor) proposes and executes a strategy for performing shortest if neighbor in closedset path calculations taking crowdsourced information, in the if tentative_g_score>= g_score[neighbor] form of imperatives and impediments, into consideration. continue The strategy is built on top of Google Maps (GM) and if neighbor not in openset or tentative_g_score
IV. SYSTEM DESIGN B.A* Algorithm The Point of the paper is to discover out the route in between any A* uses a best-first search and finds a least-cost path from a two spots inside a city entered by the client. This may be given beginning node to one objective node (out of one or implemented using a client-server design where a request having more possible objectives). As A* navigates the chart, it takes two intersections as Source and Goal is sent from client to server after a path of the least anticipated total cost or distance, and requested route is returned to client as a response from server. keeping a sorted priority queue of alternate path segments The client-server execution assumes that the client gets to the along the way. It uses a knowledge-plus-heuristic cost functional application remotely from client end to server one. This function of node (usually indicated) to decide the arrange in makes a clear thought of having client at one machine remotely which the search visits nodes in the tree. The cost function is accessing the application and server at the other. Hence the plan a whole of two functions: • the past path-cost function, which incorporates noteworthy components shown in functional project is the known distance from the beginning node to the current plan below: The client end consists of client interface from where node • a future path-cost function, which is an allowable an input is taken for processing. The server end consists of a Java "heuristic estimate" of the distance from to the goal Processing Application and Database for it.
Pseudo Code: function A*(start,goal) 99
IJRITCC | July 2018, Available @ http://www.ijritcc.org ______International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 6 Issue: 7 98 - 101 ______
The preparing application essentially takes as it were begin and end junctions and computes the route in between them with all fundamental subtle elements having middle intersections with landmarks and streets in a specific region. The Database utilized by preparing application may be a Social database containing entirety data almost city in terms B. Shortest route graphical representation: of intersections, landmarks, streets and areas. The input Graphical representation of shortest route is appeared in figure. It containing source and goal intersections for the asked route is highlighted the shortest course from source to destination. Client sent to the server conclusion as a request from client end. can utilize both the procedures to effortlessly know the route This request is inserted in a XML record can be called as between source to goal. GPI provides different strategies to get to XML request to be sent to server. At server on accepting a the highlighted route. XML request; it is provided to a XML parser for extricating fundamental information i.e. source and destination junctions which are in turn provided to Java Processing application as an input. This application computes a requested route (a most limited one) by connection with the database utilizing SQL inquiries to get vital data for computation. For a computed route to be sent to client, it is once more implanted into a XML forming a XML response. This reaction on accepting at client end is once more sent to a parser to extricate a route to be shown to the client at to user interface.
A. Shortest route in the form of text route: A client has arrangement to know the shortest way from source to goal in two ways content-based route and graphical route by utilizing Google outline. A content-based route gives correct way from source to goal in the shape of directions, turns, middle spots and distance between that spots. A path is given to client by utilizing SQL query. At last it gives the overall shortest distance from source to destination.
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IJRITCC | July 2018, Available @ http://www.ijritcc.org ______International Journal on Recent and Innovation Trends in Computing and Communication ISSN: 2321-8169 Volume: 6 Issue: 7 98 - 101 ______Department, GECM, Gujarat for their indispensable support, V. FUTURESCOPE suggestions and motivation. The downsides happened in past paper of shortest way REFERENCES discovery by utilizing Dijkstra calculation is recovered in this paper by employing A* algorithm. In this paper, we [1] By Mr. Reid “Shortest distance between two points on earth” utilize A* calculation for deciding shortest way between two http://wordpress.mrreid.org/haversine-formula/ This is an electronic document. Date of publishing 20/12/2011. junctions. But A* is heuristic in nature it implies that A* [2] Samuel Idowu, Nadeem Bari, “A Development Framework for algorithm does not grant any guaranty for great solution. Smart City,” Luleå University of Technology International This is property of any heuristic algorithm A* algorithm. So, journal of Computer Application, vol 6, 9 Nov. 2012 able to utilize any algorithm related with A* algorithm [3] Javin J. Mwemzi, YoufangHuang,” Optimal Facility location which can donate best arrangement to calculate shortest path on spherical surfaces”, New york science Journal, April 2011. between two cities. A* algorithm is combination of Dijkstra [4] Ben Gardiner, Waseem Ahmad, Travis Cooper,”Collision algorithm and Breadth First Search algorithm. In expansion Avoidance Techniques for unmanned Aerial Vehicles”, Auburn to that, A* is heuristic in nature. This System can be applied University, National Science Foundation, 08/07/2011. as a navigation system which can navigate through out city. [5] Simeon Nedkov, SisiZlatanova, “Enabling Obstacle Avoidance for Google maps”,June 2011. Together with intracity shortest path detection, we will [6] Bing Pan,john C. Crotts and Brian Muller,”Developing Web implement same concept for intercity. Based Tourism Information using Google Map” Departemnt of Huminity and Tourism Mangement,Charston ,USA. VI. CONCLUSION [7] ElinaAgapie.jason Ryder, Jeff Burke, Deborth Estrin,” “Landmark Based Routing in Indian Cities” is bound to Probable Path Interference for GPS traces in cities”, university allow the briefest route giving a junction to junction of California,2009. [8] K.M.Chandy,J. Misra, “Distributed Computation on Graphs: movement to client together with the appropriate bearings Shortest Path Algorithm”, University of Texas, March 1982. and turnings directing the client to urge the precise [9] Siemens AG. Munchen, Ulrich Lauther “An Extremely Fast intermediate junctions (with their noteworthy points of Exact Algorithm for Finding Shortest Path in static network interest) or points of interest in specific zones in between with geographic backgroung”, International journal on two junctions/spots provided by user. The client moreover Computer science and Engineering, June2006. gets correct route with direction of inserted Google Map. [10] Philip Klein,Satish Rao ,Monika Rauch, Sairam Subramnyam, “Faster Shortest Path Algorithm for Planner Graphs”, March VII. ACKNOWLEDGEMENT 1994. [11] Andrew v. Goldberg, Haim Kaplan, Renato F. Werneck, We would like to thank Government engineering college, “Efficient Point to point shortest Path Algorithm”, Internation Modasa for providing all the required amenities. I am also Research on Advance Research in Computer Science and grateful to Prof. J.S. Dhobi, Head of Information Technology Software Engineering, Oct 2005.
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